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Predicting Brain Age With Machine Learning and Transcriptome Profiling

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In this study, researchers investigated age-associated gene expression changes in the prefrontal cortex of male and female brains and used machine learning to develop age prediction models.

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The human brain is a complex organ, and its aging process is influenced by a plethora of factors, both genetic and environmental. Aging-related changes in the brain can lead to cognitive decline and susceptibility to neurodegenerative diseases. Therefore, understanding the molecular mechanisms underlying these changes is crucial for developing therapeutic strategies to delay or prevent age-related cognitive decline.

Over the past few years, a myriad of scientific studies have been conducted to understand the intricate relationship between our genes and the aging process. In a new study, researchers Joseph A. Zarrella and Amy Tsurumi from Harvard T.H. Chan School of Public Health, Massachusetts General Hospital, Harvard Medical School, and Shriner’s Hospitals for Children-Boston explored the concept of genome brain age prediction, a groundbreaking area of study that employs advanced bioinformatics tools to analyze changes in gene expression associated with aging. On February 28, 2024, their research paper was published and chosen as the cover paper for Aging’s Volume 16, Issue 5, entitled, “Genome-wide transcriptome profiling and development of age prediction models in the human brain.”

“[…] we aimed to profile transcriptome changes in the aging PFC [prefrontal cortex] overall and compare females and males, and develop prediction models for age.”

Transcriptome Profiling in the Prefrontal Cortex

The prefrontal cortex (PFC) plays a significant role in the aging process. It is responsible for a host of cognitive functions, including decision-making and planning. Throughout the aging process, significant transcriptome alterations occur in the PFC compared to other regions of the brain. These alterations can influence cognitive decline and susceptibility to neurodegenerative diseases.

Delving deeper into the complexities of aging, researchers have turned to transcriptome profiling as a powerful tool to uncover the molecular changes occurring within the prefrontal cortex. Transcriptome profiling allows scientists to measure the expression levels of all genes in a cell or tissue. By analyzing the transcriptome of the PFC, researchers can identify genes that are differentially expressed during the aging process. These genes can serve as potential biomarkers for age prediction.

The Study

In their groundbreaking research, Zarrella and Tsurumi aimed to develop prediction models for age based on the expression levels of specific panels of transcripts in the PFC. They leveraged advanced machine learning algorithms, including the least absolute shrinkage and selection operator (Lasso), Elastic Net (EN), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), to develop accurate prediction models for chronological age.

The researchers used postmortem PFC transcriptome datasets obtained from the Gene Expression Omnibus (GEO) repository, ranging in age from 21 to 105 years. They identified differentially regulated transcripts in old and elderly samples compared to young samples and assessed the genes associated with age using ontology, pathway, and network analyses.

Machine learning algorithms were used to develop accurate prediction models for chronological age based on the expression levels of specific transcripts. The study found that specific gene expression changes in the PFC are highly correlated with age. Some transcripts showed female and male-specific differences, indicating that sex may play a role in the aging process at the molecular level.

Key Findings & Implications

The study identified several key genes whose expression levels change significantly with age. These genes include Carbonic Anhydrase 4 (CA4), Calbindin 1 (CALB1), Neuropilin and Tolloid Like 2 (NETO2), and Olfactomedin1 (OLFM1), among others. Many of these genes have been previously implicated in aging or aging-related diseases, validating the results of this study.

The researchers also developed four highly accurate age prediction models using different machine learning algorithms. These models were validated in a test set and an external validation set, demonstrating their potential application in predicting chronological age based on gene expression levels.

“Our results support the notions that specific gene expression changes in the PFC are highly correlated with age, that some transcripts show female and male-specific differences, and that machine learning algorithms are useful tools for developing prediction models for age based on transcriptome information.”

Conclusions & Future Directions

This study sheds light on the complex relationship between gene expression changes and the aging process in the human brain. The findings underscore the potential of using transcriptome profiling and machine learning algorithms for age prediction. The identified genes could serve as potential biomarkers for age prediction and may offer new insights into the molecular mechanisms underlying the aging process.

However, further validation of these models in larger populations and molecular studies to elucidate the potential mechanisms by which the identified transcripts may be related to aging phenotypes would be beneficial. Additionally, more inclusive studies investigating the interplay between genetic markers and factors such as sex, lifestyle, and environmental exposures are warranted.

In conclusion, this study provides a promising foundation for future research on genome brain age prediction. It also underscores the potential of transcriptome profiling and machine learning for exploring the complex interplay between our genes and the aging process. This approach could pave the way for personalized medicine strategies aimed at preventing or delaying age-related cognitive decline and neurodegenerative diseases.

Click here to read the full research paper published in Aging.

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Aging is an open-access, traditional, peer-reviewed journal that publishes high-impact papers in all fields of aging research. All papers are available to readers (at no cost and free of subscription barriers) in bi-monthly issues at Aging-US.com.

Click here to subscribe to Aging publication updates.

For media inquiries, please contact media@impactjournals.com.

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Understanding the Mechanisms of Brain Aging and Longevity in Neurons

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In a new editorial, researchers discuss interconnected mechanisms of neuronal functionality and available tools to investigate neuronal aging and longevity. 

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Neurons, the building blocks of the nervous system, play a vital role in our body’s function and longevity. Unlike other cells, neurons do not undergo replicative aging. However, they are still susceptible to various sources of damage throughout life, leading to neuronal death. Understanding the mechanisms behind aging and neuronal death is crucial for uncovering the secrets of brain longevity and developing potential interventions to promote healthy aging.

In a new editorial, researchers Fang Fang, Robert Usselman and Renee Reijo Pera from University of Science and Technology of China, Florida Institute of Technology and McLaughlin Research Institute discussed new interconnected mechanisms of neuronal functionality and available tools to investigate neuronal aging and longevity. On December 13, 2023, their editorial was published in Aging’s Volume 15, Issue 23, entitled, “Aging and neuronal death.”

Neuronal Durability, Differentiation & Maintenance

Neurons, born during embryonic development, must function in the body for the entire lifespan of the organism. They are incredibly durable cells, but they are not immune to damage. Neurons require a significant amount of oxygen and glucose to carry out their activities, making them vulnerable to ischemia. Ischemia occurs when the blood supply to a particular tissue is restricted, leading to oxygen and nutrient deprivation. 

Neurons can accumulate damage over time, which may result in cell death linked to reactive oxygen species (ROS). Neurons may also die due to ion overload and swelling caused by the malfunction of voltage-gated ion channels on their membranes. High concentrations of neurotransmitters and the accumulation of misfolded proteins are also implicated in neuronal death, observed in various neurodegenerative diseases.

To gain insights into the factors that promote neuron differentiation and maintenance, researchers have developed innovative screening methods. For example, Cui and colleagues described a high-throughput screening method using a luciferase reporter construct inserted downstream of the endogenous tyrosine hydroxylase (TH) gene. They differentiated neurons from human pluripotent stem cells and monitored their activity over time. This approach allows for the modeling of cell survival and demise, providing valuable information about the factors that influence neuronal longevity.

The Role of ROS in Survival & Death

Reactive oxygen species (ROS) are molecules produced during normal cellular metabolism. They play a crucial role in various biological processes but can also lead to oxidative stress when their levels exceed normal functional levels. Recent research has shed light on the distinction between global and local ROS balances and imbalances in cell phenotyping and mitochondrial energy management.

While global ROS homeostasis is essential for overall cellular health, ROS signaling pathways are driven locally by cellular microdomain-specific ROS production and degradation. Neurons have developed mechanisms to control ROS production and combat oxidative stress. For example, they express neurotrophic proteins that enhance mitochondrial activity, promoting the overall health of neurons.

“A sustained disruption of ROS balance can result in desirable enhanced cell signaling or undesirable oxidative stress, which can either improve function or diminish performance, respectively.”

Mechanisms for Longevity

Neurons have evolutionarily developed intricate mechanisms to maintain their longevity. They possess a distinct transcriptome signature that represses genes related to neural excitation and synaptic function. By preventing neurons from experiencing ion overload, this mechanism contributes to their long-term survival.

These brain cells have also developed specific DNA repair mechanisms to correct errors induced by active transcription. Neurons can turn off pro-apoptotic genes through alternative splicing, avoiding apoptosis and promoting long-term survival. These interconnected mechanisms work together to reduce the accumulation of aging-related damage in neurons. Understanding the fundamental mechanisms that enable the longevity of neurons is crucial for developing interventions that promote healthy brain aging. Researchers can use novel tools, including cell-based models, imaging techniques and animal studies, to investigate these mechanisms.

Conclusions

Neurons, although durable cells, are susceptible to various forms of damage that can lead to their demise. By studying the interplay between ROS, neuronal excitation, DNA repair, and apoptosis, researchers aim to uncover the secrets of brain longevity and develop strategies to mitigate the effects of aging on neurons. By understanding these mechanisms, researchers aim to develop interventions that promote healthy brain aging and enhance our overall understanding of brain health.

“Together, these findings suggest that neurons have evolved a set of intrinsically interconnected mechanisms to reduce long-term accumulations of aging-related damages. Disruption in these mechanisms may tip the neuron homeostasis off-balance and drive the neurons into the path of degeneration. We have a plethora of tools to probe the fundamental mechanisms with hopes of translation to clinical applications.”

Click here to read the full editorial published in Aging.

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Aging is an open-access, traditional, peer-reviewed journal that has published high-impact papers in all fields of aging research since 2009. All papers are available to readers (at no cost and free of subscription barriers) in bi-monthly issues at Aging-US.com.

Click here to subscribe to Aging publication updates.

For media inquiries, please contact media@impactjournals.com.

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The Role of R-loops in Neuronal Aging

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In a new editorial, researcher Hana Hall discusses the role of R-loops in neuronal aging and neurodegeneration. 

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R-loops are structures that form when the nascent RNA hybridizes with the template DNA strand, displacing the non-template strand. In other words, R-loops are like temporary tangles in our DNA where a new RNA molecule forms by copying one of the DNA strands and pushes aside the other DNA strand. Nascent RNA refers to the newly synthesized RNA molecule that is produced during the process of transcription. In addition to transcription, R-loops are involved in various biological processes, such as splicing, DNA repair and chromatin remodeling. However, when R-loop homeostasis is disrupted, they can also cause transcriptional impairment, genome instability and cellular dysfunction.

“R-loops have been shown and studied in a wide range of organisms and while they have important regulatory roles, persistent R-loops can be detrimental to cell function and survival, having been closely linked to both gene expression dysregulation and increased genome instability.”

In a new editorial paper, researcher Hana Hall from the Purdue Institute for Integrative Neuroscience at Purdue University discusses the role of R-loops in neuronal aging and neurodegeneration. On September 13, 2023, her editorial was published in Aging’s Volume 15, Issue 17, and entitled, “R-loops in neuronal aging.” Hall summarizes her recent study and the current knowledge on how R-loop levels change during aging, how they affect gene expression and neuronal function, and how they are regulated by different factors.

“In our recent study, we demonstrated that R-loops accumulate in fly PR [photoreceptor] neurons by middle age and significantly increase into late-life stages [5].”

The Editorial

According to Hall, R-loop levels increase with age in different organisms and tissues, including neurons. This could be due to several reasons, such as reduced expression or activity of R-loop resolving enzymes (e.g., Top3β, RNase H1), increased transcriptional activity or stress, or impaired DNA repair mechanisms. Hall also highlighted that R-loop accumulation is associated with decreased expression of long and highly expressed genes, which are enriched for neuronal functions. This could lead to impaired neuronal activity and communication, as well as increased vulnerability to neurodegenerative diseases.

“Our study provides first evidence of R-loop accumulation in aging neurons and a contributing role in loss of neuronal function during aging.”

Hall further discussed how R-loop homeostasis is modulated by various factors, such as chromatin structure, epigenetic modifications, RNA-binding proteins, and non-coding RNAs. She also mentioned some potential therapeutic strategies to restore R-loop balance in aging neurons, such as overexpressing or delivering R-loop resolving enzymes, modulating chromatin accessibility or targeting specific R-loop forming genes.

Conclusions

Hall concluded that R-loops are important players in neuronal aging and neurodegeneration, and that more studies are needed to understand their molecular mechanisms and functional consequences. She also suggested that R-loop mapping could be used as a biomarker to monitor neuronal health and disease progression. This editorial provides a comprehensive overview of the current knowledge of R-loops in neuronal aging, and highlights the challenges and opportunities for future research. 

“Undoubtedly, R-loops are at the crossroads of several hallmarks of aging, namely transcriptional stress, genome instability, and chronic immune response. Targeting R-loop levels thus may help restore these pathways to a normal/healthy state and slow down or prevent the onset of age-dependent neurodegenerative diseases.”

Click here to read the full editorial published in Aging.

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Aging is an open-access, traditional, peer-reviewed journal that has published high-impact papers in all fields of aging research since 2009. All papers are available to readers (at no cost and free of subscription barriers) in bi-monthly issues at Aging-US.com.

Click here to subscribe to Aging publication updates.

For media inquiries, please contact media@impactjournals.com.

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